# JAEGIS RAVERSE MCP Server
Production-ready Model Context Protocol (MCP) server for RAVERSE - AI Multi-Agent Binary Patching System.
## 📊 Package Distribution
[](https://www.npmjs.com/package/raverse-mcp-server)
[](https://www.npmjs.com/package/raverse-mcp-server)
[](https://pypi.org/project/jaegis-raverse-mcp-server/)
[](https://pypi.org/project/jaegis-raverse-mcp-server/)
[](LICENSE)
[](https://www.python.org/)
## Overview
This MCP server exposes 35 core capabilities from RAVERSE 2.0 as standardized MCP tools, enabling seamless integration with Claude, other AI models, and external systems.
## Features
### Binary Analysis Tools (4 tools)
- **Disassemble Binary**: Convert machine code to human-readable assembly
- **Generate Code Embedding**: Create semantic vectors for code snippets
- **Apply Patch**: Programmatically modify binary files
- **Verify Patch**: Confirm patch application and integrity
### Knowledge Base & RAG Tools (4 tools)
- **Ingest Content**: Add content to knowledge base
- **Search Knowledge Base**: Find relevant content via semantic search
- **Retrieve Entry**: Get specific knowledge base entries
- **Delete Entry**: Remove entries from knowledge base
### Web Analysis Tools (5 tools)
- **Reconnaissance**: Gather intelligence about web targets
- **Analyze JavaScript**: Extract logic and API calls from JS code
- **Reverse Engineer API**: Generate OpenAPI specs from traffic
- **Analyze WASM**: Decompile and analyze WebAssembly modules
- **Security Analysis**: Identify vulnerabilities and security issues
### Infrastructure Tools (5 tools)
- **Database Query**: Execute parameterized database queries
- **Cache Operation**: Manage Redis cache operations
- **Publish Message**: Send A2A protocol messages
- **Fetch Content**: Download web content with retry logic
- **Record Metric**: Track performance metrics
### Advanced Analysis Tools (5 tools)
- **Logic Identification**: Identify logic patterns in code
- **Traffic Interception**: Intercept and analyze network traffic
- **Generate Report**: Generate comprehensive analysis reports
- **RAG Orchestration**: Execute RAG workflow
- **Deep Research**: Perform deep research on topics
### Management Tools (4 tools)
- **Version Management**: Manage component versions
- **Quality Gate**: Enforce quality standards
- **Governance Check**: Check governance rules
- **Generate Document**: Generate structured documents
### Utility Tools (5 tools)
- **URL Frontier Operation**: Manage URL frontier for crawling
- **API Pattern Matcher**: Identify API patterns in traffic
- **Response Classifier**: Classify HTTP responses
- **WebSocket Analyzer**: Analyze WebSocket communication
- **Crawl Scheduler**: Schedule crawl jobs
### System Tools (4 tools)
- **Metrics Collector**: Record performance metrics
- **Multi-Level Cache**: Manage multi-level cache
- **Configuration Service**: Access configuration
- **LLM Interface**: Interface with LLM provider
### NLP & Validation Tools (2 tools)
- **Natural Language Interface**: Process natural language commands
- **PoC Validation**: Validate vulnerabilities with PoC
**Total: 35 Tools Across 9 Categories**
## Installation
### Prerequisites
- Python 3.13+
- PostgreSQL 17 with pgvector
- Redis 8.2
- OpenRouter API key (for LLM features)
### Quick Start (Recommended)
#### Option 1: NPX (Fastest - No Installation Required)
```bash
# Run the latest version without installation
npx raverse-mcp-server@latest
# Or with specific version
npx raverse-mcp-server@1.0.2
# Verify it works
npx raverse-mcp-server@latest --version
```
#### Option 2: NPM (Global Installation)
```bash
# Install globally
npm install -g raverse-mcp-server
# Run the server
raverse-mcp-server
# Verify installation
raverse-mcp-server --version
```
#### Option 3: PyPI (Python Package)
```bash
# Install via pip
pip install jaegis-raverse-mcp-server
# Run the server
python -m jaegis_raverse_mcp_server.server
# Verify installation
python -m jaegis_raverse_mcp_server.server --version
```
#### Option 4: Docker
```bash
# Pull and run Docker image
docker run -d \
-e DATABASE_URL="postgresql://user:pass@host/db" \
-e REDIS_URL="redis://localhost:6379" \
-e OPENROUTER_API_KEY="sk-or-v1-..." \
-p 8000:8000 \
raverse/mcp-server:latest
```
### Detailed Setup (From Source)
1. **Clone and navigate to directory**:
```bash
cd jaegis-RAVERSE-mcp-server
```
2. **Create virtual environment**:
```bash
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
```
3. **Install dependencies**:
```bash
pip install -e .
```
4. **Configure environment**:
```bash
cp .env.example .env
# Edit .env with your configuration
```
### Installation Guides
- **[Complete Installation Guide](INSTALLATION.md)** - Detailed instructions for all methods
- **[Quick Start Guide](QUICKSTART.md)** - Get running in 5 minutes
- **[MCP Client Setup](MCP_CLIENT_SETUP.md)** - Configure 20+ MCP clients
## Configuration
All configuration is managed via environment variables. See `.env.example` for all available options.
### Key Settings
| Variable | Default | Description |
|----------|---------|-------------|
| `LOG_LEVEL` | INFO | Logging level (DEBUG, INFO, WARNING, ERROR) |
| `DATABASE_URL` | localhost | PostgreSQL connection string |
| `REDIS_URL` | localhost | Redis connection string |
| `LLM_API_KEY` | - | OpenRouter API key |
| `ENABLE_*` | true | Feature flags for tool categories |
## Usage
### Starting the Server
```bash
raverse-mcp-server
```
### Programmatic Usage
```python
from jaegis_raverse_mcp_server import MCPServer
server = MCPServer()
result = await server.handle_tool_call(
"disassemble_binary",
{"binary_path": "/path/to/binary"}
)
```
## Tool Reference
### Binary Analysis
#### disassemble_binary
Disassemble a binary file and extract structural information.
**Parameters:**
- `binary_path` (str): Path to binary file
- `architecture` (str, optional): Target architecture
**Returns:**
- `binary_hash`: SHA256 hash
- `file_size`: Size in bytes
- `status`: Operation status
#### generate_code_embedding
Generate semantic embedding for code content.
**Parameters:**
- `code_content` (str): Code to embed
- `model` (str): Embedding model name
**Returns:**
- `content_hash`: Content hash
- `status`: Operation status
#### apply_patch
Apply patches to binary file.
**Parameters:**
- `binary_path` (str): Binary file path
- `patches` (list): List of patch objects
- `backup` (bool): Create backup before patching
**Returns:**
- `patch_count`: Number of patches applied
- `status`: Operation status
#### verify_patch
Verify patch was applied correctly.
**Parameters:**
- `original_binary` (str): Original binary path
- `patched_binary` (str): Patched binary path
**Returns:**
- `original_hash`: Original binary hash
- `patched_hash`: Patched binary hash
- `hashes_match`: Whether hashes match
### Knowledge Base
#### ingest_content
Add content to knowledge base.
**Parameters:**
- `content` (str): Content to ingest
- `metadata` (dict, optional): Associated metadata
**Returns:**
- `content_hash`: Content hash
- `status`: Operation status
#### search_knowledge_base
Search for relevant content.
**Parameters:**
- `query` (str): Search query
- `limit` (int): Max results (1-100)
- `threshold` (float): Similarity threshold (0-1)
**Returns:**
- `query`: Original query
- `status`: Operation status
#### retrieve_entry
Get specific knowledge base entry.
**Parameters:**
- `entry_id` (str): Entry ID
**Returns:**
- `entry_id`: Entry ID
- `status`: Operation status
#### delete_entry
Delete knowledge base entry.
**Parameters:**
- `entry_id` (str): Entry ID
**Returns:**
- `entry_id`: Entry ID
- `status`: Operation status
### Web Analysis
#### reconnaissance
Perform web reconnaissance on target.
**Parameters:**
- `target_url` (str): Target URL
**Returns:**
- `target_url`: Target URL
- `status`: Operation status
#### analyze_javascript
Analyze JavaScript code.
**Parameters:**
- `js_code` (str): JavaScript code
- `deobfuscate` (bool): Deobfuscate code
**Returns:**
- `status`: Operation status
- `endpoints_found`: Number of endpoints found
#### reverse_engineer_api
Reverse engineer API from traffic.
**Parameters:**
- `traffic_data` (dict): Traffic data
- `js_analysis` (dict, optional): JS analysis results
**Returns:**
- `status`: Operation status
#### analyze_wasm
Analyze WebAssembly module.
**Parameters:**
- `wasm_data` (bytes): WASM module data
**Returns:**
- `status`: Operation status
- `wasm_size`: Module size
#### security_analysis
Perform security analysis.
**Parameters:**
- `analysis_data` (dict): Analysis data
- `check_headers` (bool): Check security headers
- `check_cves` (bool): Check for CVEs
**Returns:**
- `status`: Operation status
### Infrastructure
#### database_query
Execute database query.
**Parameters:**
- `query` (str): SQL query
- `params` (list, optional): Query parameters
**Returns:**
- `status`: Operation status
#### cache_operation
Perform cache operation.
**Parameters:**
- `operation` (str): Operation (get, set, delete, exists, clear)
- `key` (str): Cache key
- `value` (any, optional): Value for set operation
- `ttl` (int, optional): Time to live in seconds
**Returns:**
- `status`: Operation status
#### publish_message
Publish A2A message.
**Parameters:**
- `channel` (str): Channel name
- `message` (dict): Message content
**Returns:**
- `status`: Operation status
#### fetch_content
Fetch content from URL.
**Parameters:**
- `url` (str): URL to fetch
- `timeout` (int): Timeout in seconds
- `retries` (int): Number of retries
**Returns:**
- `status`: Operation status
#### record_metric
Record performance metric.
**Parameters:**
- `metric_name` (str): Metric name
- `value` (float): Metric value
- `labels` (dict, optional): Metric labels
**Returns:**
- `status`: Operation status
## Error Handling
All tools return structured error responses:
```json
{
"success": false,
"error": "Error message",
"error_code": "ERROR_TYPE"
}
```
### Error Codes
- `VALIDATION_ERROR`: Input validation failed
- `DATABASE_ERROR`: Database operation failed
- `CACHE_ERROR`: Cache operation failed
- `BINARY_ANALYSIS_ERROR`: Binary analysis failed
- `WEB_ANALYSIS_ERROR`: Web analysis failed
- `TOOL_EXECUTION_ERROR`: Tool execution failed
- `UNKNOWN_TOOL`: Tool not found
## Logging
Structured logging with JSON output. Configure via `LOG_LEVEL` environment variable.
## Performance
- **Concurrent Tasks**: Configurable via `MAX_CONCURRENT_TASKS`
- **Cache TTL**: Configurable via `CACHE_TTL_SECONDS`
- **Request Timeout**: Configurable via `REQUEST_TIMEOUT_SECONDS`
## Security
- Input validation on all parameters
- Parameterized database queries
- Secure credential management via environment variables
- No hardcoded secrets
## Distribution
RAVERSE MCP Server is available through multiple distribution channels:
### NPM Package
```bash
npm install -g @raverse/mcp-server
```
- **Package**: [@raverse/mcp-server](https://www.npmjs.com/package/@raverse/mcp-server)
- **Registry**: https://registry.npmjs.org/
### PyPI Package
```bash
pip install jaegis-raverse-mcp-server
```
- **Package**: [jaegis-raverse-mcp-server](https://pypi.org/project/jaegis-raverse-mcp-server/)
- **Registry**: https://pypi.org/
### Docker Image
```bash
docker pull raverse/mcp-server:latest
```
- **Registry**: Docker Hub
- **Image**: raverse/mcp-server
### MCP Client Integration
The server is compatible with 20+ MCP clients including:
- Claude Desktop (Anthropic)
- Cursor
- Cline (VSCode)
- Roo Code (VSCode)
- Augment Code
- Continue.dev
- Windsurf (Codeium)
- Zed Editor
- And many more...
See [MCP_CLIENT_SETUP.md](MCP_CLIENT_SETUP.md) for detailed configuration guides.
## Documentation
- **[Installation Guide](INSTALLATION.md)** - Complete installation instructions
- **[Quick Start](QUICKSTART.md)** - Get running in 5 minutes
- **[MCP Client Setup](MCP_CLIENT_SETUP.md)** - Configure 20+ MCP clients
- **[Integration Guide](INTEGRATION_GUIDE.md)** - Integrate with RAVERSE
- **[Deployment Guide](DEPLOYMENT.md)** - Production deployment
- **[Tools Registry](TOOLS_REGISTRY_COMPLETE.md)** - Complete tool reference
- **[Package Distribution](PACKAGE_DISTRIBUTION.md)** - For package maintainers
- **[Publishing Guide](PUBLISHING.md)** - Publishing to npm and PyPI
## License
MIT License - See LICENSE file for details
## Support
For issues and questions, please refer to the main RAVERSE repository.
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"description": "# JAEGIS RAVERSE MCP Server\r\n\r\nProduction-ready Model Context Protocol (MCP) server for RAVERSE - AI Multi-Agent Binary Patching System.\r\n\r\n## \ud83d\udcca Package Distribution\r\n\r\n[](https://www.npmjs.com/package/raverse-mcp-server)\r\n[](https://www.npmjs.com/package/raverse-mcp-server)\r\n[](https://pypi.org/project/jaegis-raverse-mcp-server/)\r\n[](https://pypi.org/project/jaegis-raverse-mcp-server/)\r\n[](LICENSE)\r\n[](https://www.python.org/)\r\n\r\n## Overview\r\n\r\nThis MCP server exposes 35 core capabilities from RAVERSE 2.0 as standardized MCP tools, enabling seamless integration with Claude, other AI models, and external systems.\r\n\r\n## Features\r\n\r\n### Binary Analysis Tools (4 tools)\r\n- **Disassemble Binary**: Convert machine code to human-readable assembly\r\n- **Generate Code Embedding**: Create semantic vectors for code snippets\r\n- **Apply Patch**: Programmatically modify binary files\r\n- **Verify Patch**: Confirm patch application and integrity\r\n\r\n### Knowledge Base & RAG Tools (4 tools)\r\n- **Ingest Content**: Add content to knowledge base\r\n- **Search Knowledge Base**: Find relevant content via semantic search\r\n- **Retrieve Entry**: Get specific knowledge base entries\r\n- **Delete Entry**: Remove entries from knowledge base\r\n\r\n### Web Analysis Tools (5 tools)\r\n- **Reconnaissance**: Gather intelligence about web targets\r\n- **Analyze JavaScript**: Extract logic and API calls from JS code\r\n- **Reverse Engineer API**: Generate OpenAPI specs from traffic\r\n- **Analyze WASM**: Decompile and analyze WebAssembly modules\r\n- **Security Analysis**: Identify vulnerabilities and security issues\r\n\r\n### Infrastructure Tools (5 tools)\r\n- **Database Query**: Execute parameterized database queries\r\n- **Cache Operation**: Manage Redis cache operations\r\n- **Publish Message**: Send A2A protocol messages\r\n- **Fetch Content**: Download web content with retry logic\r\n- **Record Metric**: Track performance metrics\r\n\r\n### Advanced Analysis Tools (5 tools)\r\n- **Logic Identification**: Identify logic patterns in code\r\n- **Traffic Interception**: Intercept and analyze network traffic\r\n- **Generate Report**: Generate comprehensive analysis reports\r\n- **RAG Orchestration**: Execute RAG workflow\r\n- **Deep Research**: Perform deep research on topics\r\n\r\n### Management Tools (4 tools)\r\n- **Version Management**: Manage component versions\r\n- **Quality Gate**: Enforce quality standards\r\n- **Governance Check**: Check governance rules\r\n- **Generate Document**: Generate structured documents\r\n\r\n### Utility Tools (5 tools)\r\n- **URL Frontier Operation**: Manage URL frontier for crawling\r\n- **API Pattern Matcher**: Identify API patterns in traffic\r\n- **Response Classifier**: Classify HTTP responses\r\n- **WebSocket Analyzer**: Analyze WebSocket communication\r\n- **Crawl Scheduler**: Schedule crawl jobs\r\n\r\n### System Tools (4 tools)\r\n- **Metrics Collector**: Record performance metrics\r\n- **Multi-Level Cache**: Manage multi-level cache\r\n- **Configuration Service**: Access configuration\r\n- **LLM Interface**: Interface with LLM provider\r\n\r\n### NLP & Validation Tools (2 tools)\r\n- **Natural Language Interface**: Process natural language commands\r\n- **PoC Validation**: Validate vulnerabilities with PoC\r\n\r\n**Total: 35 Tools Across 9 Categories**\r\n\r\n## Installation\r\n\r\n### Prerequisites\r\n- Python 3.13+\r\n- PostgreSQL 17 with pgvector\r\n- Redis 8.2\r\n- OpenRouter API key (for LLM features)\r\n\r\n### Quick Start (Recommended)\r\n\r\n#### Option 1: NPX (Fastest - No Installation Required)\r\n```bash\r\n# Run the latest version without installation\r\nnpx raverse-mcp-server@latest\r\n\r\n# Or with specific version\r\nnpx raverse-mcp-server@1.0.2\r\n\r\n# Verify it works\r\nnpx raverse-mcp-server@latest --version\r\n```\r\n\r\n#### Option 2: NPM (Global Installation)\r\n```bash\r\n# Install globally\r\nnpm install -g raverse-mcp-server\r\n\r\n# Run the server\r\nraverse-mcp-server\r\n\r\n# Verify installation\r\nraverse-mcp-server --version\r\n```\r\n\r\n#### Option 3: PyPI (Python Package)\r\n```bash\r\n# Install via pip\r\npip install jaegis-raverse-mcp-server\r\n\r\n# Run the server\r\npython -m jaegis_raverse_mcp_server.server\r\n\r\n# Verify installation\r\npython -m jaegis_raverse_mcp_server.server --version\r\n```\r\n\r\n#### Option 4: Docker\r\n```bash\r\n# Pull and run Docker image\r\ndocker run -d \\\r\n -e DATABASE_URL=\"postgresql://user:pass@host/db\" \\\r\n -e REDIS_URL=\"redis://localhost:6379\" \\\r\n -e OPENROUTER_API_KEY=\"sk-or-v1-...\" \\\r\n -p 8000:8000 \\\r\n raverse/mcp-server:latest\r\n```\r\n\r\n### Detailed Setup (From Source)\r\n\r\n1. **Clone and navigate to directory**:\r\n```bash\r\ncd jaegis-RAVERSE-mcp-server\r\n```\r\n\r\n2. **Create virtual environment**:\r\n```bash\r\npython -m venv venv\r\nsource venv/bin/activate # On Windows: venv\\Scripts\\activate\r\n```\r\n\r\n3. **Install dependencies**:\r\n```bash\r\npip install -e .\r\n```\r\n\r\n4. **Configure environment**:\r\n```bash\r\ncp .env.example .env\r\n# Edit .env with your configuration\r\n```\r\n\r\n### Installation Guides\r\n\r\n- **[Complete Installation Guide](INSTALLATION.md)** - Detailed instructions for all methods\r\n- **[Quick Start Guide](QUICKSTART.md)** - Get running in 5 minutes\r\n- **[MCP Client Setup](MCP_CLIENT_SETUP.md)** - Configure 20+ MCP clients\r\n\r\n## Configuration\r\n\r\nAll configuration is managed via environment variables. See `.env.example` for all available options.\r\n\r\n### Key Settings\r\n\r\n| Variable | Default | Description |\r\n|----------|---------|-------------|\r\n| `LOG_LEVEL` | INFO | Logging level (DEBUG, INFO, WARNING, ERROR) |\r\n| `DATABASE_URL` | localhost | PostgreSQL connection string |\r\n| `REDIS_URL` | localhost | Redis connection string |\r\n| `LLM_API_KEY` | - | OpenRouter API key |\r\n| `ENABLE_*` | true | Feature flags for tool categories |\r\n\r\n## Usage\r\n\r\n### Starting the Server\r\n\r\n```bash\r\nraverse-mcp-server\r\n```\r\n\r\n### Programmatic Usage\r\n\r\n```python\r\nfrom jaegis_raverse_mcp_server import MCPServer\r\n\r\nserver = MCPServer()\r\nresult = await server.handle_tool_call(\r\n \"disassemble_binary\",\r\n {\"binary_path\": \"/path/to/binary\"}\r\n)\r\n```\r\n\r\n## Tool Reference\r\n\r\n### Binary Analysis\r\n\r\n#### disassemble_binary\r\nDisassemble a binary file and extract structural information.\r\n\r\n**Parameters:**\r\n- `binary_path` (str): Path to binary file\r\n- `architecture` (str, optional): Target architecture\r\n\r\n**Returns:**\r\n- `binary_hash`: SHA256 hash\r\n- `file_size`: Size in bytes\r\n- `status`: Operation status\r\n\r\n#### generate_code_embedding\r\nGenerate semantic embedding for code content.\r\n\r\n**Parameters:**\r\n- `code_content` (str): Code to embed\r\n- `model` (str): Embedding model name\r\n\r\n**Returns:**\r\n- `content_hash`: Content hash\r\n- `status`: Operation status\r\n\r\n#### apply_patch\r\nApply patches to binary file.\r\n\r\n**Parameters:**\r\n- `binary_path` (str): Binary file path\r\n- `patches` (list): List of patch objects\r\n- `backup` (bool): Create backup before patching\r\n\r\n**Returns:**\r\n- `patch_count`: Number of patches applied\r\n- `status`: Operation status\r\n\r\n#### verify_patch\r\nVerify patch was applied correctly.\r\n\r\n**Parameters:**\r\n- `original_binary` (str): Original binary path\r\n- `patched_binary` (str): Patched binary path\r\n\r\n**Returns:**\r\n- `original_hash`: Original binary hash\r\n- `patched_hash`: Patched binary hash\r\n- `hashes_match`: Whether hashes match\r\n\r\n### Knowledge Base\r\n\r\n#### ingest_content\r\nAdd content to knowledge base.\r\n\r\n**Parameters:**\r\n- `content` (str): Content to ingest\r\n- `metadata` (dict, optional): Associated metadata\r\n\r\n**Returns:**\r\n- `content_hash`: Content hash\r\n- `status`: Operation status\r\n\r\n#### search_knowledge_base\r\nSearch for relevant content.\r\n\r\n**Parameters:**\r\n- `query` (str): Search query\r\n- `limit` (int): Max results (1-100)\r\n- `threshold` (float): Similarity threshold (0-1)\r\n\r\n**Returns:**\r\n- `query`: Original query\r\n- `status`: Operation status\r\n\r\n#### retrieve_entry\r\nGet specific knowledge base entry.\r\n\r\n**Parameters:**\r\n- `entry_id` (str): Entry ID\r\n\r\n**Returns:**\r\n- `entry_id`: Entry ID\r\n- `status`: Operation status\r\n\r\n#### delete_entry\r\nDelete knowledge base entry.\r\n\r\n**Parameters:**\r\n- `entry_id` (str): Entry ID\r\n\r\n**Returns:**\r\n- `entry_id`: Entry ID\r\n- `status`: Operation status\r\n\r\n### Web Analysis\r\n\r\n#### reconnaissance\r\nPerform web reconnaissance on target.\r\n\r\n**Parameters:**\r\n- `target_url` (str): Target URL\r\n\r\n**Returns:**\r\n- `target_url`: Target URL\r\n- `status`: Operation status\r\n\r\n#### analyze_javascript\r\nAnalyze JavaScript code.\r\n\r\n**Parameters:**\r\n- `js_code` (str): JavaScript code\r\n- `deobfuscate` (bool): Deobfuscate code\r\n\r\n**Returns:**\r\n- `status`: Operation status\r\n- `endpoints_found`: Number of endpoints found\r\n\r\n#### reverse_engineer_api\r\nReverse engineer API from traffic.\r\n\r\n**Parameters:**\r\n- `traffic_data` (dict): Traffic data\r\n- `js_analysis` (dict, optional): JS analysis results\r\n\r\n**Returns:**\r\n- `status`: Operation status\r\n\r\n#### analyze_wasm\r\nAnalyze WebAssembly module.\r\n\r\n**Parameters:**\r\n- `wasm_data` (bytes): WASM module data\r\n\r\n**Returns:**\r\n- `status`: Operation status\r\n- `wasm_size`: Module size\r\n\r\n#### security_analysis\r\nPerform security analysis.\r\n\r\n**Parameters:**\r\n- `analysis_data` (dict): Analysis data\r\n- `check_headers` (bool): Check security headers\r\n- `check_cves` (bool): Check for CVEs\r\n\r\n**Returns:**\r\n- `status`: Operation status\r\n\r\n### Infrastructure\r\n\r\n#### database_query\r\nExecute database query.\r\n\r\n**Parameters:**\r\n- `query` (str): SQL query\r\n- `params` (list, optional): Query parameters\r\n\r\n**Returns:**\r\n- `status`: Operation status\r\n\r\n#### cache_operation\r\nPerform cache operation.\r\n\r\n**Parameters:**\r\n- `operation` (str): Operation (get, set, delete, exists, clear)\r\n- `key` (str): Cache key\r\n- `value` (any, optional): Value for set operation\r\n- `ttl` (int, optional): Time to live in seconds\r\n\r\n**Returns:**\r\n- `status`: Operation status\r\n\r\n#### publish_message\r\nPublish A2A message.\r\n\r\n**Parameters:**\r\n- `channel` (str): Channel name\r\n- `message` (dict): Message content\r\n\r\n**Returns:**\r\n- `status`: Operation status\r\n\r\n#### fetch_content\r\nFetch content from URL.\r\n\r\n**Parameters:**\r\n- `url` (str): URL to fetch\r\n- `timeout` (int): Timeout in seconds\r\n- `retries` (int): Number of retries\r\n\r\n**Returns:**\r\n- `status`: Operation status\r\n\r\n#### record_metric\r\nRecord performance metric.\r\n\r\n**Parameters:**\r\n- `metric_name` (str): Metric name\r\n- `value` (float): Metric value\r\n- `labels` (dict, optional): Metric labels\r\n\r\n**Returns:**\r\n- `status`: Operation status\r\n\r\n## Error Handling\r\n\r\nAll tools return structured error responses:\r\n\r\n```json\r\n{\r\n \"success\": false,\r\n \"error\": \"Error message\",\r\n \"error_code\": \"ERROR_TYPE\"\r\n}\r\n```\r\n\r\n### Error Codes\r\n\r\n- `VALIDATION_ERROR`: Input validation failed\r\n- `DATABASE_ERROR`: Database operation failed\r\n- `CACHE_ERROR`: Cache operation failed\r\n- `BINARY_ANALYSIS_ERROR`: Binary analysis failed\r\n- `WEB_ANALYSIS_ERROR`: Web analysis failed\r\n- `TOOL_EXECUTION_ERROR`: Tool execution failed\r\n- `UNKNOWN_TOOL`: Tool not found\r\n\r\n## Logging\r\n\r\nStructured logging with JSON output. Configure via `LOG_LEVEL` environment variable.\r\n\r\n## Performance\r\n\r\n- **Concurrent Tasks**: Configurable via `MAX_CONCURRENT_TASKS`\r\n- **Cache TTL**: Configurable via `CACHE_TTL_SECONDS`\r\n- **Request Timeout**: Configurable via `REQUEST_TIMEOUT_SECONDS`\r\n\r\n## Security\r\n\r\n- Input validation on all parameters\r\n- Parameterized database queries\r\n- Secure credential management via environment variables\r\n- No hardcoded secrets\r\n\r\n## Distribution\r\n\r\nRAVERSE MCP Server is available through multiple distribution channels:\r\n\r\n### NPM Package\r\n```bash\r\nnpm install -g @raverse/mcp-server\r\n```\r\n- **Package**: [@raverse/mcp-server](https://www.npmjs.com/package/@raverse/mcp-server)\r\n- **Registry**: https://registry.npmjs.org/\r\n\r\n### PyPI Package\r\n```bash\r\npip install jaegis-raverse-mcp-server\r\n```\r\n- **Package**: [jaegis-raverse-mcp-server](https://pypi.org/project/jaegis-raverse-mcp-server/)\r\n- **Registry**: https://pypi.org/\r\n\r\n### Docker Image\r\n```bash\r\ndocker pull raverse/mcp-server:latest\r\n```\r\n- **Registry**: Docker Hub\r\n- **Image**: raverse/mcp-server\r\n\r\n### MCP Client Integration\r\n\r\nThe server is compatible with 20+ MCP clients including:\r\n- Claude Desktop (Anthropic)\r\n- Cursor\r\n- Cline (VSCode)\r\n- Roo Code (VSCode)\r\n- Augment Code\r\n- Continue.dev\r\n- Windsurf (Codeium)\r\n- Zed Editor\r\n- And many more...\r\n\r\nSee [MCP_CLIENT_SETUP.md](MCP_CLIENT_SETUP.md) for detailed configuration guides.\r\n\r\n## Documentation\r\n\r\n- **[Installation Guide](INSTALLATION.md)** - Complete installation instructions\r\n- **[Quick Start](QUICKSTART.md)** - Get running in 5 minutes\r\n- **[MCP Client Setup](MCP_CLIENT_SETUP.md)** - Configure 20+ MCP clients\r\n- **[Integration Guide](INTEGRATION_GUIDE.md)** - Integrate with RAVERSE\r\n- **[Deployment Guide](DEPLOYMENT.md)** - Production deployment\r\n- **[Tools Registry](TOOLS_REGISTRY_COMPLETE.md)** - Complete tool reference\r\n- **[Package Distribution](PACKAGE_DISTRIBUTION.md)** - For package maintainers\r\n- **[Publishing Guide](PUBLISHING.md)** - Publishing to npm and PyPI\r\n\r\n## License\r\n\r\nMIT License - See LICENSE file for details\r\n\r\n## Support\r\n\r\nFor issues and questions, please refer to the main RAVERSE repository.\r\n\r\n",
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